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目的建立一项简易的绝经后妇女低骨量筛选的方法。方法经筛选获得405名上海市绝经后健康妇女,填写有关低骨量危险因素的问卷调查表,并使用双能 X 线吸收仪测定股骨颈骨密度(BMD)以诊断骨质疏松(T 值≤-2.5)。将股骨颈 BMD 与危险因素进行单元回归分析,得到有统计学意义的变量与股骨颈 BMD 进行多元回归分析,以进一步剔除无统计学意义的变量,将筛选出来的变量建立筛选指数模型,应用此模型中的变量计算筛选指数(Index)。将筛选指数做工作特征曲线(ROC 曲线),分析曲线下面积(AUC),决定最终模型的参数。结果建立筛选指数仅由年龄和体重两个参数组成。筛选指数=2×体重(kg)/10+[-1×年龄(岁)/10]。这项 Index 的灵敏度为93.4%,特异度为52.6%,它的 AUC 为0.818(95%可信度:0.766～0.870)。高危险人群组骨质疏松的患病率为58%,中等危险人群和低危险人群的患病率各为26%和2%。结论此筛选方法,可以帮助临床简便评价绝经后妇女的骨量状况,筛选出骨质疏松高危和低危人群。对低危险人群组,可能不必进行 BMD 检查,以节省检测费用。
Objective To establish a simple method for low bone mass screening in postmenopausal women. Methods A total of 405 healthy postmenopausal women in Shanghai were selected by screening. Questionnaires of risk factors for low bone mass were completed. BMD of femoral neck was measured by dual energy X-ray absorptiometry to diagnose osteoporosis (T ≤ -2.5). The BMD of femoral neck and risk factors were analyzed by unit regression, and statistically significant variables were obtained by multiple regression analysis with BMD of femoral neck to further eliminate the variables without statistical significance. The selected variables were used to establish the screening index model. Variables in the model are calculated by screening index. The screening index is used as the working characteristic curve (ROC curve), the area under the curve (AUC) is analyzed to determine the parameters of the final model. Results The establishment of screening index consisted of only two parameters, age and weight. Screening index = 2 × body weight (kg) / 10 + [- 1 × age (years) / 10]. The Index has a sensitivity of 93.4% and a specificity of 52.6%. Its AUC is 0.818 (95% confidence level: 0.766-0.870). The prevalence of osteoporosis in the high-risk group was 58%, while the prevalence was 26% and 2% in the middle- and low-risk groups, respectively. Conclusion This screening method can help clinicians easily evaluate the bone mass status of postmenopausal women and screen out the high-risk and low-risk population of osteoporosis. For low-risk groups, BMD testing may not be necessary to save testing costs.